We use the open source tool ERRANT [1]} to analyze the F\(_{0.5}\)  score of the two models for correcting different types of errors. The results of using pre-training data or not are shown in Figure REF , respectively. Comparing the two groups of experiments, we can see that the model pre-training with synthetic data has better performance in most error types than that without using synthetic data. Especially in Verb Inflection (VERB:INFL), Pronoun (PRON), Preposition (PREP), Morphology (MORPH) and Conjunction (CONJ) errors, scores increased by more than 10 percent. However, the model performance declines 5 percent in terms of word order (WO) errors. This may be due to the fact that our data synthesis method does not produce more word order errors. In future experiments, we will consider using the method of disrupting the order of sentences.
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